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Human DNA methylation data have been used to develop biomarkers of ageing, referred to as 'epigenetic clocks', which have been widely used to identify differences between chronological age and biological age in health and disease including neurodegeneration, dementia and other brain phenotypes. Existing DNA methylation clocks have been shown to be highly accurate in blood but are less precise when used in older samples or in tissue types not included in training the model, including brain. We aimed to develop a novel epigenetic clock that performs optimally in human cortex tissue and has the potential to identify phenotypes associated with biological ageing in the brain. We generated an extensive dataset of human cortex DNA methylation data spanning the life course (n = 1397, ages = 1 to 108 years). This dataset was split into 'training' and 'testing' samples (training: n = 1047; testing: n = 350). DNA methylation age estimators were derived using a transformed version of chronological age on DNA methylation at specific sites using elastic net regression, a supervised machine learning method. The cortical clock was subsequently validated in a novel independent human cortex dataset (n = 1221, ages = 41 to 104 years) and tested for specificity in a large whole blood dataset (n = 1175, ages = 28 to 98 years). We identified a set of 347 DNA methylation sites that, in combination, optimally predict age in the human cortex. The sum of DNA methylation levels at these sites weighted by their regression coefficients provide the cortical DNA methylation clock age estimate. The novel clock dramatically outperformed previously reported clocks in additional cortical datasets. Our findings suggest that previous associations between predicted DNA methylation age and neurodegenerative phenotypes might represent false positives resulting from clocks not robustly calibrated to the tissue being tested and for phenotypes that become manifest in older ages. The age distribution and tissue type of samples included in training datasets need to be considered when building and applying epigenetic clock algorithms to human epidemiological or disease cohorts. [ABSTRACT FROM AUTHOR]

Background: As the most stable and experimentally accessible epigenetic mark, DNA methylation is of great interest to the research community. The landscape of DNA methylation across tissues, through development and in disease pathogenesis is not yet well characterized. Thus there is a need for rapid and cost effective methods for assessing genome-wide levels of DNA methylation. The Illumina Infinium HumanMethylation450 (450K) BeadChip is a very useful addition to the available methods for DNA methylation analysis but its complex design, incorporating two different assay methods, requires careful consideration. Accordingly, several normalization schemes have been published. We have taken advantage of known DNA methylation patterns associated with genomic imprinting and X-chromosome inactivation (XCI), in addition to the performance of SNP genotyping assays present on the array, to derive three independent metrics which we use to test alternative schemes of correction and normalization. These metrics also have potential utility as quality scores for datasets. Results: The standard index of DNA methylation at any specific CpG site is β = M/(M + U + 100) where M and U are methylated and unmethylated signal intensities, respectively. Betas (βs) calculated from raw signal intensities (the default GenomeStudio behavior) perform well, but using 11 methylomic datasets we demonstrate that quantile normalization methods produce marked improvement, even in highly consistent data, by all three metrics. The commonly used procedure of normalizing betas is inferior to the separate normalization of M and U, and it is also advantageous to normalize Type I and Type II assays separately. More elaborate manipulation of quantiles proves to be counterproductive. Conclusions: Careful selection of preprocessing steps can minimize variance and thus improve statistical power, especially for the detection of the small absolute DNA methylation changes likely associated with complex disease phenotypes. For the convenience of the research community we have created a user-friendly R software package called wateRmelon, downloadable from bioConductor, compatible with the existing methylumi, minfi and IMA packages, that allows others to utilize the same normalization methods and data quality tests on 450K data. [ABSTRACT FROM AUTHOR]

Background: miRNAs are short single-stranded non-coding RNAs involved in post-transcriptional gene regulation that play a major role in normal biological functions and diseases. Little is currently known about how expression of miRNAs is regulated. We surveyed variation in miRNA abundance in the hippocampus of mouse inbred strains, allowing us to take a genetic approach to the study of miRNA regulation, which is novel for miRNAs. The BXD recombinant inbred panel is a very well characterized genetic reference panel which allows quantitative trait locus (QTL) analysis of miRNA abundance and detection of correlates in a large store of brain and behavioural phenotypes. Results: We found five suggestive trans QTLs for the regulation of miRNAs investigated. Further analysis of these QTLs revealed two genes, Tnik and Phf17, under the miR-212 regulatory QTLs, whose expression levels were significantly correlated with miR-212 expression. We found that miR-212 expression is correlated with cocaine related behaviour, consistent with a reported role for this miRNA in the control of cocaine consumption. miR-31 is correlated with anxiety and alcohol related behaviours. KEGG pathway analysis of each miRNA’s expression correlates revealed enrichment of pathways including MAP kinase, cancer, long-term potentiation, axonal guidance and WNT signalling. Conclusions: The BXD reference panel allowed us to establish genetic regulation and characterize biological function of specific miRNAs. QTL analysis enabled detection of genetic loci that regulate the expression of these miRNAs. eQTLs that regulate miRNA abundance are a new mechanism by which genetic variation influences brain and behaviour. Analysis of one of these QTLs revealed a gene, Tnik, which may regulate the expression of a miRNA, a molecular pathway and a behavioural phenotype. Evidence of genetic covariation of miR-212 abundance and cocaine related behaviours is strongly supported by previous functional studies, demonstrating the value of this approach for discovery of new functional roles and downstream processes regulated by miRNA. [ABSTRACT FROM AUTHOR]

Background: Insulin-like growth factor 2 (Igf2) is a paternally expressed imprinted gene regulating fetal growth, playing an integral role in the development of many tissues including the brain. The parent-of-origin specific expression of Igf2 is largely controlled by allele-specific DNA methylation at CTCF-binding sites in the imprinting control region (ICR), located immediately upstream of the neighboring H19 gene. Previously we reported evidence of a negative correlation between DNA methylation in this region and cerebellum weight in humans. Results: We quantified cerebellar DNA methylation across all four CTCF binding sites spanning the murine Igf2/H19 ICR in an outbred population of Heterogeneous Stock (HS) mice (n = 48). We observe that DNA methylation at the second and third CTCF binding sites in the Igf2/H19 ICR shows a negative relationship with cerebellar mass, reflecting the association observed in human post-mortem cerebellum tissue. Conclusions: Given the important role of the cerebellum in motor control and cognition, and the link between structural cerebellar abnormalities and neuropsychiatric phenotypes, the identification of epigenetic factors associated with cerebellum growth and development may provide important insights about the etiology of psychiatric disorders. [ABSTRACT FROM AUTHOR]

Gene Set Enrichment (GSE) is a computational technique which determines whether a priori defined set of genes show statistically significant differential expression between two phenotypes. Currently, the gene sets used for GSE are derived from annotation or pathway databases, which often contain computationally based and unrepresentative data. Here, we propose a novel approach for the generation of comprehensive and biologically derived gene sets, deriving sets through the application of machine learning techniques to gene expression data. These gene sets can be produced for specific tissues, developmental stages or environments. They provide a powerful and functionally meaningful way in which to mine genomewide association and next generation sequencing data in order to identify disease-associated variants and pathways. [ABSTRACT FROM AUTHOR]

Micro-RNAs (miRNAs) are short, single-stranded, noncoding RNAs that are involved in the regulation of protein-coding genes at the level of messenger RNA (mRNA). They are involved in the regulation of numerous traits, including developmental timing, apoptosis, immune function, and neuronal development. To better understand how the expression of the miRNAs themselves is regulated, we looked for miRNA expression differences among four mouse inbred strains, A/J, BALB/cJ, C57BL/6J, and DBA/2J, in one tissue, the hippocampus. A total of 166 miRNA RT-PCR assays were used to screen RNA pools for each strain. Twenty miRNA species that were markedly different between strains were further investigated using eight individual samples per strain, and 11 miRNAs showed significant differences across strains ( p < 0.05). This is the first observation of miRNA expression differences across inbred mice strains. We conducted an in silico correlation analysis of the expression of these differentially expressed miRNAs with phenotype data and mRNA expression to better characterise the effects of these miRNAs on both phenotype and the regulation of mRNA expression. This approach has allowed us to nominate miRNAs that have potential roles in anxiety, exploration, and learning and memory. [ABSTRACT FROM AUTHOR]

PWD/Ph is an inbred mouse strain derived from wild mice trapped in central Czech Republic. These mice are of the Mus musculus musculus subspecies, whose ancestors separated from those of Mus musculus domesticus about one million years ago. There is a high degree of variation in the genomic sequence and a wide range of phenotypes between PWD/Ph and standard laboratory inbred mouse strains, the genomes of which are principally Mus musculus domesticus in origin, making PWD/Ph mice an useful resource for complex trait research. As a first step in taking advantage of this resource, a preliminary characterization of the behavior of PWD/Ph mice was performed. Groups of 10 PWD/Ph and C57BL/6J male mice were tested in the open field, novel object exploration task and Morris water maze. PWD/Ph were marginally more anxious than C57BL/6J mice in the open field but subsequently displayed much higher levels of exploration and lower anxiety than C57BL/6J mice following introduction of a novel object. As C57BL/6J itself is rated as highly explorative among classical inbred strains, PWD/Ph probably represents an extreme among mouse strains for this specific behavior. PWD/Ph and C57BL/6J mice differed in their water escape training profiles in the Morris water maze, perhaps reflecting different motivational factors. However, there were no differences in overall cognitive ability (spatial learning) as both groups learned to find the hidden platform and performed equally well when the location of the platform was changed. This is the first quantification of the behavior of PWD/Ph mice and the results are promising for the potential of the consomic panel currently being generated with PWD/Ph and C57BL/6J as a tool for the molecular dissection of behavior. [ABSTRACT FROM AUTHOR]

Mouse inbred strains differ in many aspects of their phenotypes, and it is known that gene expression does so too. This gives us an opportunity to isolate the genetic aspect of variation in expression and compare it to other phenotypic variables. We have investigated these issues using an eight-strain expression profile comparison with four replicates per strain on Affymetrix MGU74av2 GeneChips focusing on one well-defined brain tissue (the hippocampus). We identified substantial strain-specific variation in hippocampal gene expression, with more than two hundred genes showing strain differences by a very conservative criterion. Many such genetically driven differences in gene expression are likely to result in functional differences including differences in behaviour A large panel of inbred strains could be used to identify genes functionally involved in particular phenotypes, similar to genetic correlation. The genetic correlation between expression profiles and function is potentially very powerful, especially given the current large-scale generation of phenotypic data on multiple strains (the Mouse Phenome Project). As an example, the strongest genetic correlation between more than 200 probe sets showing significant differences among our eight inbred strains and a ranking of these strains by aggression phenotype was found for Comt a gene known to be involved in aggression. [ABSTRACT FROM AUTHOR]

Objective: Advanced paternal age (APA) at conception has been linked with autism and schizophrenia in offspring, neurodevelopmental disorders that affect social functioning. The current study explored the effects of paternal age on social development in the general population.Method: We used multilevel growth modeling to investigate APA effects on socioemotional development from early childhood until adolescence, as measured by the Strengths and Difficulties Questionnaire (SDQ) in the Twins Early Development Study (TEDS) sample. We also investigated genetic and environmental underpinnings of the paternal age effects on development, using the Additive genetics, Common environment, unique Environment (ACE) and gene-environment (GxE) models.Results: In the general population, both very young and advanced paternal ages were associated with altered trajectory of social development (intercept: p = .01; slope: p = .03). No other behavioral domain was affected by either young or advanced age at fatherhood, suggesting specificity of paternal age effects. Increased importance of genetic factors in social development was recorded in the offspring of older but not very young fathers, suggesting distinct underpinnings of the paternal age effects at these two extremes.Conclusion: Our findings highlight that the APA-related deficits that lead to autism and schizophrenia are likely continuously distributed in the population. [ABSTRACT FROM AUTHOR]

The floating head (flh) gene in zebrafish encodes a homeodomain protein, which is essential for notochord formation along the entire body axis. flh orthologs, termed Not genes, have been isolated from chick and Xenopus, but no mammalian ortholog has yet been identified. Truncate (tc) is an autosomal recessive mutation in mouse that specifically disrupts the development of the caudal notochord. Here, we demonstrate that truncate arose by a mutation in the mouse Not gene. The truncate allele (Nottc) contains a point mutation in the homeobox of Not that changes a conserved Phenylalanine residue in helix 1 to a Cysteine (F20C), and significantly destabilizes the homeodomain. Reversion of F20C in one allele of homozygous tc embryonic stem (ES) cells is sufficient to restore normal notochord formation in completely ES cell-derived embryos. We have generated a targeted mutation of Not by replacing most of the Not coding sequence, including the homeobox with the eGFP gene. The phenotype of NoteGFP/eGFP NoteGFP/tc, and Nottc/tc embryos is very similar but slightly more severe in NoteGFP/eGFP than in Nottc/tc embryos. This confirms allelism of truncate and Not, and indicates that tc is not a complete null allele. Not expression is abolished in Foxa2 and T mutant embryos, suggesting that Not acts downstream of both genes during notochord development. This is in contrast to zebrafish embryos, in which flh interacts with ntl (zebrafish T) in a regulatory loop and is essential for development of the entire notochord, and suggests that different genetic control circuits act in different vertebrate species during notochord formation. [ABSTRACT FROM AUTHOR]